A Single-Handed Partial Zooming Technique for Touch-Screen Mobile Devices

Despite its ubiquitous use, the pinch zooming technique is not effective for one-handed interaction. We propose ContextZoom, a novel technique for single-handed zooming on touch-screen mobile devices. It allows users to specify any place on a device screen as the zooming center to ensure that the intended zooming target is always visible on the screen after zooming. ContextZoom supports zooming in/out a portion of a viewport, and provides a quick switch between the partial and whole viewports. We conducted an empirical evaluation of ContextZoom through a controlled lab experiment to compare ContextZoom and the Google maps’ single-handed zooming technique. Results show that ContextZoom outperforms the latter in task completion time and the number of discrete actions taken. Participants also reported higher levels of perceived effectiveness and overall satisfaction with ContextZoom than with the Google maps’ single-handed zooming technique, as well as a similar level of perceived ease of use

Predicting and Reducing the Impact of Errors in Character-Based Text Entry

This dissertation focuses on the effect of errors in character-based text entry techniques. The effect of errors is targeted from theoretical, behavioral, and practical standpoints. This document starts with a review of the existing literature. It then presents results of a user study that investigated the effect of different error correction conditions on popular text entry performance metrics. Results showed that the way errors are handled has a significant effect on all frequently used error metrics. The outcomes also provided an understanding of how users notice and correct errors. Building on this, the dissertation then presents a new high-level and method-agnostic model for predicting the cost of error correction with a given text entry technique. Unlike the existing models, it accounts for both human and system factors and is general enough to be used with most character-based techniques. A user study verified the model through measuring the effects of a faulty keyboard on text entry performance. Subsequently, the work then explores the potential user adaptation to a gesture recognizer’s misrecognitions in two user studies. Results revealed that users gradually adapt to misrecognition errors by replacing the erroneous gestures with alternative ones, if available. Also, users adapt to a frequently misrecognized gesture faster if it occurs more frequently than the other error-prone gestures. Finally, this work presents a new hybrid approach to simulate pressure detection on standard touchscreens. The new approach combines the existing touch-point- and time-based methods. Results of two user studies showed that it can simulate pressure detection more reliably for at least two pressure levels: regular (~1 N) and extra (~3 N). Then, a new pressure-based text entry technique is presented that does not require tapping outside the virtual keyboard to reject an incorrect or unwanted prediction. Instead, the technique requires users to apply extra pressure for the tap on the next target key. The performance of the new technique was compared with the conventional technique in a user study. Results showed that for inputting short English phrases with 10% non-dictionary words, the new technique increases entry speed by 9% and decreases error rates by 25%. Also, most users (83%) favor the new technique over the conventional one. Together, the research presented in this dissertation gives more insight into on how errors affect text entry and also presents improved text entry methods

Two one-handed tilting-based writing techniques on a smartphone

Text entry is a vital part of operating a mobile device, and is often done using a virtual keyboard such as QWERTY. Text entry using the virtual keyboard often faces difficulties, as the size of a single button is small and intangible, which can lead to high error rates and low text entry speed. This thesis reports a user experiment of two novel tilting-based text entry techniques with and without button press for key selection. The experiment focused on two main issues: 1) the performance of the tilting-based methods in comparison to the current commonly used reference method, the virtual QWERTY keyboard; and 2) evaluation of subjective satisfaction of the novel methods. The experiment was conducted using TEMA software running on an Android smartphone with a relativity small screen size. All writing was done with one hand only. The participants were able to comprehend and learn to use the new methods without any major problems. The development of text entry skill with the new methods was clear, as the mean text entry rates improved by 63-80 percent. The reference method QWERTY remained fastest of the three throughout the experiment. The tilting-based technique with key press for selection had the lowest total error rate at the end of the experiment, closely followed by QWERTY. Interview and questionnaire results showed that in some cases the tilting-based method was the preferred method of the three. Many of the shortcomings of tilt-based methods found during the experiment can be addressed in further development, and these methods are likely to prove competitive on devices with very small displays. Tilting has a potential as part of other interaction techniques besides text entry, and could be used to increase bandwidth between the device and the user without significantly increasing the cognitive load